Integrative analysis of high dimensional tissue molecular data to define key biological systems in autoimmune diseases (SBC)

高维组织分子数据综合分析，定义自身免疫性疾病 (SBC) 的关键生物系统

• 批准号: 10687728
• 负责人: Soumya Raychaudhuri
• 金额: $ 28.29万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-03-18 至 2026-12-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10687728
• 关键词: Algorithms; Autoimmune; Autoimmune Diseases; Automobile Driving; B-Lymphocytes; Blood specimen; CD8-Positive T-Lymphocytes; Cells; Cellular Assay; Clinical; Clinical Data; Collaborations; Communities; Complex; Computational Biology; Computing Methodologies; Consultations; Cues; Data; Data Analyses; Data Set; Development; Disease; Education; Ensure; Epigenetic Process; Fibroblasts; Genetic; Genomics; Goals; HLA-DR Antigens; Helper-Inducer T-Lymphocyte; Histologic; Hospitals; Immune; Individual; Inflammation; Inflammatory; International; Leadership; Mediating; Medicine; Methods; Modality; Molecular; Nephritis; Outcome; Pathway interactions; Patients; Peripheral; Phenotype; Positioning Attribute; Process; Proteins; Proteomics; Psoriasis; Quality Control; Reproducibility; Research; Rheumatism; Rheumatoid Arthritis; Rheumatology; Sampling; Sjogren' s Syndrome; Statistical Methods; Supervision; System; Systemic Lupus Erythematosus; Systems Biology; Technology; Tissue Model; Tissue Sample; Tissues; Training; Transcript; Validation; Woman; algorithm development; analytical method; bioinformatics tool; biological systems; complex data; computerized tools; data integration; data resource; experience; high dimensionality; human disease; innovation; investigator training; multidimensional data; multimodal data; multimodality; novel; novel strategies; programs; success; text searching; tool; transcriptomics

PROJECT SUMMARY/ABSTRACT Here we propose a Systems Biology Core (SBC) for the Accelerating Medicines Partnerships in Autoimmune and Immune-Mediated Diseases (AMP AIM). The AMP AIM will use high dimensional molecular and cellular assays to define the key cell states, pathways, and molecular components of tissue inflammation and damage by examining patient tissue and blood samples. Ultimately, we seek to define the components of tissue inflammation in autoimmune and inflammatory diseases including psoriatic spectrum diseases (PSD), rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), Sjogren’s syndrome (SS), and other related conditions. AMP RA/SLE initiated this process by querying 106 single cells in inflamed RA synovial and SLE nephritis tissue samples using multimodal strategies; it defined key cell states in tissue inflammation, including T peripheral helper T cells (Tph), GZMK+ CD8+ T cells, HLA-DR+THY1+ fibroblasts, and autoimmune- associated B cells (ABCs). Now, to understand how these and emerging cell-states function and interact to cause disease, it will be essential to obtain high dimensional data on patient sample data across a spectrum of diseases and disease sub-phenotypes. These data may capture the cellular states; the spatial localization of cell states, proteins and transcripts; histological features; and other tissue parameters. A powerful and skilled team that is able to define strategies to analyze this data, integrate multiple modalities of data, and integrate results from across a diverse set of diseases and tissues will be essential to the success of this program. We build from our experience leading the Systems Biology Group within the Accelerating Medicines Partnerships Rheumatoid Arthritis and Systemic Lupus Erythematosus (AMP RA/SLE). We have built a team that is skilled at analysis of diverse modalities and computational biology. We have specific experience and expertise in inflammatory diseases. Here we propose to: (1) Develop Tools and Technology to analyze high dimensional cellular and molecular data. This includes optimizing existing bioinformatics and computational tools. It also includes developing new computational and statistical methods to integrate high dimensional data manifestation of disease. (2) Enable collaboration throughout the network and facilitate systems level analysis. We envision that this is an integrated activity with the network, where we will devise and ultimately create an integrated model of tissue inflammation across diseases to define features that drive clinical disease. This will require the development of new statistical and computational methods. It will also require tight collaboration within the network including data synchronization, storage, sharing, and clinical data integration. In addition, we will engage the network by offering consultation, technical support and training in high dimensional data analysis. .

项目概要/摘要 在这里，我们提出了一个系统生物学核心（SBC），用于加速自身免疫领域的药物合作 AMP AIM 将使用高维分子和细胞。 确定组织炎症和损伤的关键细胞状态、途径和分子成分的测定 通过检查患者组织和血液样本，我们最终试图确定组织的成分。 自身免疫性炎症和炎症性疾病，包括银屑病谱系疾病 (PSD)， 类风湿性关节炎（RA）、系统性红斑狼疮（SLE）、干燥综合征（SS）和其他相关疾病 AMP RA/SLE 通过查询发炎的 RA 滑膜和 SLE 中的 106 个单细胞来启动此过程。 使用多模式策略的肾炎组织样本；它定义了组织炎症的关键细胞状态，包括 T 外周辅助 T 细胞 (Tph)、GZMK+ CD8+ T 细胞、HLA-DR+THY1+ 成纤维细胞和自身免疫细胞 现在，了解这些细胞和新兴细胞状态如何发挥作用并相互作用。 导致疾病，因此必须获得一系列患者样本数据的高维数据 这些数据可以捕获细胞状态； 细胞状态、蛋白质和转录本；以及其他组织参数。 能够定义策略来分析这些数据、集成多种数据模式并集成 来自不同疾病和组织的结果对于该计划的成功至关重要。 我们借鉴了在加速药物领域领导系统生物学小组的经验 类风湿性关节炎和系统性红斑狼疮 (AMP RA/SLE) 合作伙伴关系 我们已经建立了一个团队。 擅长分析多种模式和计算生物学，我们拥有特定的经验和能力。 在此，我们建议： (1) 开发分析高维细胞和分子数据的工具和技术。 优化现有的生物信息学和计算工具还包括开发新的。 整合疾病高维数据表现的计算和统计方法。 (2) 实现整个网络的协作并促进系统级分析。 是一项与网络的集成活动，我们将设计并最终创建一个集成的 跨疾病的组织炎症模型，以确定驱动临床疾病的特征。 需要开发新的统计和计算方法。 网络内的协作，包括数据同步、存储、共享和临床数据 此外，我们将通过提供咨询、技术支持和整合来参与网络。 高维数据分析培训。 。